Affiliations: [a] College of Science, Hebei Agricultural University, Baoding, China
| [b] School of Information Technology and Management, University of International Business and Economics, Beijing, China
Correspondence:
[*]
Corresponding author. Yaodong Ni, School of Information Technology and Management, University of International Business and Economics, Beijing, 100029, China. E-mail: ni@uibe.edu.cn.
Note: [†] These authors contributed equally to this work.
Abstract: This paper studies the pricing and low-carbon decision problems in a supply chain containing a manufacturer and a downstream retailer. The manufacturer produces a single product under the cap-and-trade scheme. We formulate the price and carbon-concerned demand function. To maximize their revenue, the manufacturer and the retailer determine their selling prices and carbon emission reduction rates separately. Due to the fast product updates speed, some parameters do not have enough historical data. For example, the sales cost of the retailer, the demand of consumers, and the total carbon emissions of manufacturers are far from frequency stability. This fact makes the distribution function obtained in practice usually deviate from the frequency. They are all uncertain variables whose distributions are estimated from the empirical data of experts or managers. In this paper, we give three decentralized game models to explore the equilibrium behaviors in the corresponding decision environment under an uncertain environment. Corresponding analytical solutions are offered under different game scenarios. Finally, numerical experiments are performed to illustrate the effectiveness of the established models and yield some remarkable insights.
Keywords: Supply chain management, Pricing decision, Cap-and-trade, Low-carbon, Stackelberg game
